North Atlantic Oscillation

Observed data . Reanalysis . Satellite data . Model  results NAO

NAO signal

Climate prediction problem

Linear models

Data Analysis

Climate variability

Climate predictability

Methodology

Predictive signals

The linear modelling approach is based on identification of joint modes of variability linking predictor and predictand variables.

  • A subset of CCA pairs representing two fields is used to build a regression model (Von Storch, 1995) to estimate the anomalies of predictand (SLP, geopotential height at 500 hPa) from the anomalies of the predictor (May SST, November air surface temperature).

  • The performance of the model is sensitively dependent on the number of EOFs and CCA pairs used in the regression model.

  • Here, the CCA based models have been been trained for the interval 1961-1986 and were independently tested in the interval 1987-2001. Both models use 4 CCA modes derived from 6 EOFs from the paired fields.

Results

References:

Bojariu, R., L.Gimeno, 2003: Predictability and numerical modelling of the North Atlantic Oscillation. Earth Science Reviews, Vol 63/1-2, 145-168.

Bojariu, R., Paliu D.,Gavrilescu T., Toma L., R. Povara 2000: Climate and economical aspects of drought prediction in Romania in the sustainable development perspective. In Proceedings book of the Central and Eastern European Workhop on Drought Mitigation ( L. Vermes and A. Szemessy eds.) ,12-15 Aprilie 2000, Budapest-Felsogod, Ungaria , 235-238.

 

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